class_docstr: A wrapper for torch.optim.Optimizer objects that helps with managing dynamically generated parameters.
  
  :param optim_constructor: a torch.optim.Optimizer
  :param optim_args: a dictionary of learning arguments for the optimizer or a callable that returns
      such dictionaries
  :param clip_args: a dictionary of clip_norm and/or clip_value args or a callable that returns
      such dictionaries
docstr: :param filename: file name to load from
  :type filename: str
  :param map_location: torch.load() map_location parameter
  :type map_location: function, torch.device, string or a dict
  
  Load optimizer state from disk
docstr_tok: [":","param","filename",":","file","name","to","load","from",":","type","filename",":","str",":","param","map_location",":","torch.load","(",")","map_location","parameter",":","type","map_location",":","function",",","torch.device",",","string","or","a","dict","Load","optimizer","state","from","disk"]
code: def load(self, filename: str, map_location=None) -> None:
      """
      :param filename: file name to load from
      :type filename: str
      :param map_location: torch.load() map_location parameter
      :type map_location: function, torch.device, string or a dict
  
      Load optimizer state from disk
      """
      with open(filename, "rb") as input_file:
          state = torch.load(input_file, map_location=map_location)
      self.set_state(state)
  
imports: import inspect
  from typing import Any, Callable, Dict, Iterable, List, Optional, Type, Union, ValuesView
  import torch
  from torch import Tensor
  from torch.nn.utils import clip_grad_norm_, clip_grad_value_
  from torch.optim import Optimizer
  import pyro
  from pyro.optim.adagrad_rmsprop import AdagradRMSProp
  from pyro.optim.clipped_adam import ClippedAdam
  from pyro.optim.dct_adam import DCTAdam
  from pyro.params.param_store import module_from_param_with_module_name, normalize_param_name, user_param_name
label_desc: Use image node_id 6 for calling the PyroOptim obj's underlying member method code with example usage: obj.load(filename, map_location) without return types